Résumé
The prediction of protein structures is an important problem in molecular biology. In spite of the large efforts from the research community, and of the recent development of artificial intelligence tools specifically designed for this problem, a complete and definitive solution to the problem has not been found yet. This work is based on the observation that many tools for the prediction of protein conformations rely on both local and non-local geometrical information, even though the non-local information can be very hard to identify within the desired precision in some particular situations. For this reason, we explore in this work the effect of local geometry on methods capable of constructing protein conformations. This initial study has the final aim of devising new alternative methods where the predictions may be guided mainly by the local geometry of proteins.
| langue originale | Anglais |
|---|---|
| Pages (de - à) | 677-681 |
| Nombre de pages | 5 |
| journal | Annals of Computer Science and Intelligence Systems |
| Numéro de publication | 2024 |
| Les DOIs | |
| état | Publié - 1 janv. 2024 |
| Evénement | 19th Conference on Computer Science and Intelligence Systems, FedCSIS 2024 - Belgrade, Serbie Durée: 8 sept. 2024 → 11 sept. 2024 |
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